Empathy and perspective taking
Processing
Ian Hussey
18 December 2024
Reworking of Marcus’ code
Dependencies
Anonymise data
Run only the first time, before data sharing
Rename and select
data_trimmed <- data_raw %>%
rename(
# rename "Q" to PET, rename attention checks items
PET_1 = Q2,
PET_2 = Q4,
PET_3 = Q6,
PET_4 = Q8,
PET_5 = Q10,
PET_6 = Q12,
PET_7 = Q14,
attention_check_1 = IRI_24,
# Because of the attention check item, all IRI_items after 24 have to be renamed
IRI_24 = IRI_25,
IRI_25 = IRI_26,
IRI_26 = IRI_27,
IRI_27 = IRI_28,
IRI_28 = IRI_29,
attention_check_2 = EQ_60,
# Because of the attention check item, EQ Item 61 has to be renamed
EQ_60 = EQ_61,
PTTA_1 = PTT.A_test1,
PTTA_2 = PTT.A_test2,
PTTA_3 = PTT.A_test3,
PTTA_4 = PTT.A_test4,
PTTA_5 = PTT.A_test5,
PTTA_6 = PTT.A_test6,
PTTA_7 = PTT.A_test7,
PTTA_8 = PTT.A_test8,
PTTA_9 = PTT.A_test9,
PTTA_10 = PTT.A_test10,
PTTA_11 = PTT.A_test11,
PTTA_12 = PTT.A_test12,
PTTA_13 = PTT.A_test13,
PTTA_14 = PTT.A_test14,
PTTA_15 = PTT.A_test15,
PTTA_16 = PTT.A_test16,
PTTA_17 = PTT.A_test17,
PTTA_18 = PTT.A_test18,
PTTA_19 = PTT.A_test19,
PTTA_20 = PTT.A_test20,
PTTA_21 = PTT.A_test21,
PTTA_22 = PTT.A_test22,
PTTA_23 = PTT.A_test23,
PTTA_24 = PTT.A_test24,
PTTA_25 = PTT.A_test25,
PTTA_26 = PTT.A_test26,
PTTA_27 = PTT.A_test27,
PTTA_28 = PTT.A_test28,
PTTA_29 = PTT.A_test29,
PTTA_30 = PTT.A_test30,
PTTA_31 = PTT.A_test31,
PTTA_32 = PTT.A_test32
) |>
# wrangle gender
mutate(gender = ifelse(Gender == "self-identified:", Gender_3_TEXT, Gender)) |>
# select variables of interest
select(unique_id,
timepoint,
age = Age_1,
gender,
attention_check_1,
attention_check_2,
SITES,
starts_with("IRI_"),
starts_with("EQ_"),
starts_with("PET_"),
starts_with("EYES_"),
starts_with("PTP_"),
starts_with("PTTA_")) |>
# drop meta data columns
select(!ends_with(".Click") & !ends_with(".Submit") & !ends_with(".Count")) |>
# drop filler and sample items
select(!all_of(c("EYES_0",
"EQ_2", "EQ_3", "EQ_5", "EQ_7", "EQ_9", "EQ_13", "EQ_16", "EQ_17", "EQ_20", "EQ_23",
"EQ_24", "EQ_30", "EQ_31", "EQ_33", "EQ_40", "EQ_45", "EQ_47", "EQ_51", "EQ_53", "EQ_56"))) Convert all responses to numeric
data_recoded <- data_trimmed |>
# age
mutate(age = as.numeric(age)) |>
# attention checks
mutate(attention_check_1 = ifelse(attention_check_1 == "C", "passed", "failed"),
attention_check_2 = ifelse(attention_check_2 == "strongly agree", "passed", "failed")) |>
# SITES
mutate(SITES = recode(SITES,
'1 Not very true of me' = 1,
'2' = 2,
'3' = 3,
'4' = 4,
'5 Very true of me.' = 5)) |>
# IRI
mutate(across(
all_of(c("IRI_1", "IRI_2", "IRI_5", "IRI_6", "IRI_8", "IRI_9", "IRI_10", "IRI_11", "IRI_16", "IRI_17",
"IRI_20", "IRI_21", "IRI_22", "IRI_23", "IRI_24", "IRI_25", "IRI_26", "IRI_27", "IRI_28")),
~ recode(.x,
'A - DOES NOT DESCRIBE ME VERY WELL' = 0,
'B' = 1,
'C' = 2,
'D' = 3,
'E - DESCRIBES ME VERY WELL' = 4)
)) |>
mutate(across(
all_of(c("IRI_3", "IRI_4", "IRI_7", "IRI_12", "IRI_13", "IRI_14", "IRI_15", "IRI_18", "IRI_19")),
~ recode(.x,
'A - DOES NOT DESCRIBE ME VERY WELL' = 4,
'B' = 3,
'C' = 2,
'D' = 1,
'E - DESCRIBES ME VERY WELL' = 0)
)) |>
# EQ
mutate(across(
all_of(c("EQ_1", "EQ_6", "EQ_19", "EQ_22", "EQ_25", "EQ_26", "EQ_35", "EQ_36", "EQ_37", "EQ_38",
"EQ_41", "EQ_42", "EQ_43", "EQ_44", "EQ_52", "EQ_54", "EQ_55", "EQ_57", "EQ_58", "EQ_59", "EQ_60")),
~ recode(.x,
'strongly agree' = 2,
'slightly agree' = 1,
'slightly disagree' = 0,
'strongly disagree' = 0)
)) |>
mutate(across(
all_of(c("EQ_4", "EQ_8", "EQ_10", "EQ_11", "EQ_12", "EQ_14", "EQ_15", "EQ_18", "EQ_21", "EQ_27", "EQ_28",
"EQ_29", "EQ_32", "EQ_34", "EQ_39", "EQ_46", "EQ_48", "EQ_49", "EQ_50")),
~ recode(.x,
'strongly agree' = 2,
'slightly agree' = 1,
'slightly disagree' = 0,
'strongly disagree' = 0)
)) |>
# PET
mutate(across(
starts_with("PET_"),
~ recode(.x,
'not at all' = 1,
'a little bit' = 2,
'it arouses some feelings' = 3,
'quite a lot' = 4,
'very much' = 5)
)) |>
# EYES
mutate(EYES_1 = recode(EYES_1, 'playful' = 1, .default = 0),
EYES_2 = recode(EYES_2, 'upset' = 1, .default = 0),
EYES_3 = recode(EYES_3, 'desire' = 1, .default = 0),
EYES_4 = recode(EYES_4, 'insisting' = 1, .default = 0),
EYES_5 = recode(EYES_5, 'worried' = 1, .default = 0),
EYES_6 = recode(EYES_6, 'fantasizing' = 1, .default = 0),
EYES_7 = recode(EYES_7, 'uneasy' = 1, .default = 0),
EYES_8 = recode(EYES_8, 'despondent' = 1, .default = 0),
EYES_9 = recode(EYES_9, 'preoccupied' = 1, .default = 0),
EYES_10 = recode(EYES_10, 'cautious' = 1, .default = 0),
EYES_11 = recode(EYES_11, 'regretful' = 1, .default = 0),
EYES_12 = recode(EYES_12, 'sceptical' = 1, .default = 0),
EYES_13 = recode(EYES_13, 'anticipating' = 1, .default = 0),
EYES_14 = recode(EYES_14, 'accusing' = 1, .default = 0),
EYES_15 = recode(EYES_15, 'contemplative' = 1, .default = 0),
EYES_16 = recode(EYES_16, 'thoughtful' = 1, .default = 0),
EYES_17 = recode(EYES_17, 'doubtful' = 1, .default = 0),
EYES_18 = recode(EYES_18, 'decisive' = 1, .default = 0),
EYES_19 = recode(EYES_19, 'tentative' = 1, .default = 0),
EYES_20 = recode(EYES_20, 'friendly' = 1, .default = 0),
EYES_21 = recode(EYES_21, 'fantasizing' = 1, .default = 0),
EYES_22 = recode(EYES_22, 'preoccupied' = 1, .default = 0),
EYES_23 = recode(EYES_23, 'defiant' = 1, .default = 0),
EYES_24 = recode(EYES_24, 'pensive' = 1, .default = 0),
EYES_25 = recode(EYES_25, 'interested' = 1, .default = 0),
EYES_26 = recode(EYES_26, 'hostile' = 1, .default = 0),
EYES_27 = recode(EYES_27, 'cautious' = 1, .default = 0),
EYES_28 = recode(EYES_28, 'interested' = 1, .default = 0),
EYES_29 = recode(EYES_29, 'reflective' = 1, .default = 0),
EYES_30 = recode(EYES_30, 'flirtatious' = 1, .default = 0),
EYES_31 = recode(EYES_31, 'confident' = 1, .default = 0),
EYES_32 = recode(EYES_32, 'serious' = 1, .default = 0),
EYES_33 = recode(EYES_33, 'concerned' = 1, .default = 0),
EYES_34 = recode(EYES_34, 'distrustful' = 1, .default = 0),
EYES_35 = recode(EYES_35, 'nervous' = 1, .default = 0),
EYES_36 = recode(EYES_36, 'suspicious' = 1, .default = 0)) |>
# McHugh Perspective Taking Protocol
mutate(PTP_1 = recode(PTP_1, 'Red Lego brick' = 1, .default = 0),
PTP_2 = recode(PTP_2, 'Black chair' = 1, .default = 0),
PTP_3 = recode(PTP_3, 'Watching television' = 1, .default = 0),
PTP_4 = recode(PTP_4, 'Green Lego brick' = 1, .default = 0),
PTP_5 = recode(PTP_5, 'Blue chair' = 1, .default = 0),
PTP_6 = recode(PTP_6, 'Reading' = 1, .default = 0),
#PTP_7 = recode(PTP_7, 'Black chair' = 1, .default = 0), # this item was incorrectly implemented in the survey as a single reversed trial not a double
PTP_7 = recode(PTP_7, 'Blue chair' = 1, .default = 0),
PTP_8 = recode(PTP_8, 'Black chair' = 1, .default = 0),
PTP_9 = recode(PTP_9, 'Watching television' = 1, .default = 0)) |>
# Perspective Taking Task for Adults (PTT-A) - ALL 'CORRECT' RESPONSES NEED CHECKING AGAINST JAMIE'S CODE
mutate(PTTA_1 = recode(PTTA_1, 'Picture 6' = 1, .default = 0),
PTTA_2 = recode(PTTA_2, 'Picture 4' = 1, .default = 0),
PTTA_3 = recode(PTTA_3, 'Picture 1' = 1, .default = 0),
PTTA_4 = recode(PTTA_4, 'Picture 8' = 1, .default = 0),
PTTA_5 = recode(PTTA_5, 'Picture 3' = 1, .default = 0),
PTTA_6 = recode(PTTA_6, 'Picture 2' = 1, .default = 0),
PTTA_7 = recode(PTTA_7, 'Picture 7' = 1, .default = 0),
PTTA_8 = recode(PTTA_8, 'Picture 3' = 1, .default = 0),
PTTA_9 = recode(PTTA_9, 'Picture 1' = 1, .default = 0),
PTTA_10 = recode(PTTA_10, 'Picture 2' = 1, .default = 0),
PTTA_11 = recode(PTTA_11, 'Picture 7' = 1, .default = 0),
PTTA_12 = recode(PTTA_12, 'Picture 8' = 1, .default = 0),
PTTA_13 = recode(PTTA_13, 'Picture 5' = 1, .default = 0),
PTTA_14 = recode(PTTA_14, 'Picture 6' = 1, .default = 0),
PTTA_15 = recode(PTTA_15, 'Picture 4' = 1, .default = 0),
PTTA_16 = recode(PTTA_16, 'Picture 3' = 1, .default = 0),
PTTA_17 = recode(PTTA_17, 'Picture 3' = 1, .default = 0),
PTTA_18 = recode(PTTA_18, 'Picture 6' = 1, .default = 0),
PTTA_19 = recode(PTTA_19, 'Picture 5' = 1, .default = 0),
PTTA_20 = recode(PTTA_20, 'Picture 2' = 1, .default = 0),
PTTA_21 = recode(PTTA_21, 'Picture 8' = 1, .default = 0),
PTTA_22 = recode(PTTA_22, 'Picture 1' = 1, .default = 0),
PTTA_23 = recode(PTTA_23, 'Picture 4' = 1, .default = 0),
PTTA_24 = recode(PTTA_24, 'Picture 7' = 1, .default = 0),
PTTA_25 = recode(PTTA_25, 'Picture 4' = 1, .default = 0),
PTTA_26 = recode(PTTA_26, 'Picture 5' = 1, .default = 0),
PTTA_27 = recode(PTTA_27, 'Picture 1' = 1, .default = 0), # ??
PTTA_28 = recode(PTTA_28, 'Picture 2' = 1, .default = 0), # ??
PTTA_29 = recode(PTTA_29, 'Picture 4' = 1, .default = 0), # ??
PTTA_30 = recode(PTTA_30, 'Picture 8' = 1, .default = 0), # ??
PTTA_31 = recode(PTTA_31, 'Picture 6' = 1, .default = 0), # ??
PTTA_32 = recode(PTTA_32, 'Picture 5' = 1, .default = 0)) # ??
# checks
table(data_trimmed$SITES, data_recoded$SITES)##
## 1 2 3 4 5
## 1 Not very true of me 1 0 0 0 0
## 2 0 8 0 0 0
## 3 0 0 29 0 0
## 4 0 0 0 113 0
## 5 Very true of me. 0 0 0 0 86##
## 0 1 2 3 4
## 0 0 0 0 0
## A - DOES NOT DESCRIBE ME VERY WELL 8 0 0 0 0
## B 0 15 0 0 0
## C 0 0 47 0 0
## D 0 0 0 99 0
## E - DESCRIBES ME VERY WELL 0 0 0 0 67##
## 0 1 2 3 4
## 0 0 0 0 0
## A - DOES NOT DESCRIBE ME VERY WELL 0 0 0 0 74
## B 0 0 0 74 0
## C 0 0 55 0 0
## D 0 25 0 0 0
## E - DESCRIBES ME VERY WELL 8 0 0 0 0##
## 0 1 2
## 0 0 0
## slightly agree 0 104 0
## slightly disagree 19 0 0
## strongly agree 0 0 106
## strongly disagree 6 0 0##
## 0 1 2
## 0 0 0
## slightly agree 0 39 0
## slightly disagree 110 0 0
## strongly agree 0 0 23
## strongly disagree 63 0 0##
## 1 2 3 4 5
## 0 0 0 0 0
## a little bit 0 19 0 0 0
## it arouses some feelings 0 0 19 0 0
## not at all 4 0 0 0 0
## quite a lot 0 0 0 57 0
## very much 0 0 0 0 136##
## 0 1
## 2 0
## arrogant 25 0
## cautious 0 168
## joking 6 0
## reassuring 36 0##
## 0 1
## 2 0
## Black chair 47 0
## Blue chair 0 188##
## 0 1
## 5 0
## Picture 1 13 0
## Picture 2 2 0
## Picture 3 3 0
## Picture 4 9 0
## Picture 5 1 0
## Picture 6 6 0
## Picture 7 7 0
## Picture 8 0 191Calculate total scores
data_processed <- data_recoded |>
# SITES
mutate(SITES_completeness = ifelse(!is.na(SITES), "complete", "partial")) |>
# IRI
mutate(IRI_completeness = ifelse(rowSums(across(starts_with("IRI_"), ~ !is.na(.x))) == 28, "complete", "partial"),
IRI_FS = IRI_1 + IRI_5 + IRI_7 + IRI_12 + IRI_16 + IRI_26 + IRI_23,
IRI_EC = IRI_2 + IRI_4 + IRI_9 + IRI_14 + IRI_18 + IRI_20 + IRI_22,
IRI_PT = IRI_3 + IRI_8 + IRI_11 + IRI_15 + IRI_21 + IRI_25 + IRI_28,
IRI_PD = IRI_6 + IRI_10 + IRI_13 + IRI_17 + IRI_19 + IRI_24 + IRI_27,
IRI_total = IRI_FS + IRI_EC + IRI_PT + IRI_PD) |>
# EQ
mutate(EQ_completeness = ifelse(rowSums(across(starts_with("EQ_"), ~ !is.na(.x))) == 40, "complete", "partial"),
EQ_total = EQ_1 + EQ_4 + EQ_6 + EQ_8 + EQ_10 + EQ_11 + EQ_12 + EQ_14 + EQ_15 + EQ_18 + EQ_19 + EQ_21 + EQ_22 + EQ_25 +
EQ_26 + EQ_27 + EQ_28 + EQ_29 + EQ_32 + EQ_34 + EQ_35 + EQ_36 + EQ_37 + EQ_38 + EQ_39 + EQ_41 + EQ_42 + EQ_43 + EQ_44 +
EQ_46 + EQ_48 + EQ_49 + EQ_50 + EQ_52 + EQ_54 + EQ_55 + EQ_57 + EQ_58 + EQ_59 + EQ_60 ) |>
# PET - the mean score is calculated
mutate(PET_completeness = ifelse(rowSums(across(starts_with("PET_"), ~ !is.na(.x))) == 7, "complete", "partial"),
PET_total = (PET_1 + PET_2 + PET_3 + PET_4 + PET_5 + PET_6 + PET_7)/7) |>
# EYES
mutate(EYES_completeness = ifelse(rowSums(across(starts_with("EYES_"), ~ !is.na(.x))) == 36, "complete", "partial"),
EYES_total = EYES_1 + EYES_2 + EYES_3 + EYES_4 + EYES_5 + EYES_6 + EYES_7 + EYES_8 + EYES_9 + EYES_10 +
EYES_11 + EYES_12 + EYES_13 + EYES_14 + EYES_15 + EYES_16 + EYES_17 + EYES_18 + EYES_19 + EYES_20 +
EYES_21 + EYES_22 + EYES_23 + EYES_24 + EYES_25 + EYES_26 + EYES_27 + EYES_28 + EYES_29 + EYES_30 +
EYES_31 + EYES_32 + EYES_33 + EYES_34 + EYES_35 + EYES_36) |>
# # PTP
# mutate(PTP_completeness = ifelse(rowSums(across(starts_with("PTP_"), ~ !is.na(.x))) == 9, "complete", "partial"),
# PTP_simple = PTP_1 + PTP_2 + PTP_3,
# PTP_reversed = PTP_4 + PTP_5 + PTP_6,
# PTP_doublereversed = PTP_7 + PTP_8 + PTP_9,
# PTP_total = PTP_1 + PTP_2 + PTP_3 + PTP_4 + PTP_5 + PTP_6 + PTP_7 + PTP_8 + PTP_9) |>
# PTP
mutate(PTP_completeness = ifelse(rowSums(across(starts_with("PTP_"), ~ !is.na(.x))) == 9, "complete", "partial"),
PTP_simple = PTP_1 + PTP_2 + PTP_3,
PTP_reversed = PTP_4 + PTP_5 + PTP_6 + PTP_7, # PTP_7 was incorrectly implemented as a single reversed trial instead of double. corrected here.
PTP_doublereversed = PTP_8 + PTP_9, # PTP_7 was incorrectly implemented as a single reversed trial instead of double. corrected here.
PTP_total = PTP_1 + PTP_2 + PTP_3 + PTP_4 + PTP_5 + PTP_6 + PTP_7 + PTP_8 + PTP_9) |>
# PTT-A
# note: no completeness check as it is a timed test where not all items are answered
mutate(PTTA_total = PTTA_1 + PTTA_2 + PTTA_3 + PTTA_4 + PTTA_5 + PTTA_6 + PTTA_7 + PTTA_8 + PTTA_9 + PTTA_10 + PTTA_11 + PTTA_12 + PTTA_13 + PTTA_14 + PTTA_15 + PTTA_16 + PTTA_17 + PTTA_18 + PTTA_19 + PTTA_20 + PTTA_21 + PTTA_22 + PTTA_23 + PTTA_24 + PTTA_25 + PTTA_26 + PTTA_27 + PTTA_28 + PTTA_29 + PTTA_30 + PTTA_31 + PTTA_32) |>
# master exclude
mutate(exclude_master = ifelse(attention_check_1 == "passed" &
attention_check_2 == "passed" &
SITES_completeness == "complete" &
IRI_completeness == "complete" &
EQ_completeness == "complete" &
PET_completeness == "complete" &
EYES_completeness == "complete" &
PTP_completeness == "complete",
"include",
"exclude")) |>
# reorder
select(unique_id,
timepoint,
age, gender,
# exclusion variables
exclude_master, attention_check_1, attention_check_2, SITES_completeness, IRI_completeness, EQ_completeness, PET_completeness, EYES_completeness, PTP_completeness,
# (sub)scale scores
SITES, IRI_FS, IRI_EC, IRI_PT, IRI_PD, IRI_total, EQ_total, PET_total, EYES_total, PTP_simple, PTP_reversed, PTP_doublereversed, PTP_total, PTTA_total,
# item level scores
IRI_1, IRI_2, IRI_3, IRI_4, IRI_5, IRI_6, IRI_7, IRI_8, IRI_9, IRI_10, IRI_11, IRI_12, IRI_13, IRI_14, IRI_15,
IRI_16, IRI_17, IRI_18, IRI_19, IRI_20, IRI_21, IRI_22, IRI_23, IRI_24, IRI_25, IRI_26, IRI_27, IRI_28,
EQ_1, EQ_4, EQ_6, EQ_8, EQ_10, EQ_11, EQ_12, EQ_14, EQ_15, EQ_18, EQ_19, EQ_21, EQ_22, EQ_25, EQ_26, EQ_27,
EQ_28, EQ_29, EQ_32, EQ_34, EQ_35, EQ_36, EQ_37, EQ_38, EQ_39, EQ_41, EQ_42, EQ_43, EQ_44, EQ_46, EQ_48, EQ_49,
EQ_50, EQ_52, EQ_54, EQ_55, EQ_57, EQ_58, EQ_59, EQ_60,
PET_1, PET_2, PET_3, PET_4, PET_5, PET_6, PET_7,
EYES_1, EYES_2, EYES_3, EYES_4, EYES_5, EYES_6, EYES_7, EYES_8, EYES_9, EYES_10, EYES_11, EYES_12, EYES_13, EYES_14,
EYES_15, EYES_16, EYES_17, EYES_18, EYES_19, EYES_20, EYES_21, EYES_22, EYES_23, EYES_24, EYES_25, EYES_26, EYES_27,
EYES_28, EYES_29, EYES_30, EYES_31, EYES_32, EYES_33, EYES_34, EYES_35, EYES_36,
PTP_1, PTP_2, PTP_3, PTP_4, PTP_5, PTP_6, PTP_7, PTP_8, PTP_9,
PTTA_1, PTTA_2, PTTA_3, PTTA_4, PTTA_5, PTTA_6, PTTA_7, PTTA_8,
PTTA_9, PTTA_10, PTTA_11, PTTA_12, PTTA_13, PTTA_14, PTTA_15, PTTA_16,
PTTA_17, PTTA_18, PTTA_19, PTTA_20, PTTA_21, PTTA_22, PTTA_23, PTTA_24,
PTTA_25, PTTA_26, PTTA_27, PTTA_28, PTTA_29, PTTA_30, PTTA_31, PTTA_32)Sanity checks - item correlations
dat <- data_processed |>
filter(timepoint == 1)
dat |>
select(starts_with("IRI")) |>
correlation() |>
summary() |>
plot(show_data = "points")
Session info
## R version 4.3.3 (2024-02-29)
## Platform: aarch64-apple-darwin20 (64-bit)
## Running under: macOS 15.2
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.11.0
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## time zone: Europe/Zurich
## tzcode source: internal
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] insight_0.19.10 see_0.8.3 correlation_0.8.4 tidyr_1.3.1
## [5] dplyr_1.1.4 readr_2.1.5
##
## loaded via a namespace (and not attached):
## [1] sandwich_3.1-0 sass_0.4.9 utf8_1.2.4 generics_0.1.3
## [5] lattice_0.22-6 hms_1.1.3 digest_0.6.37 magrittr_2.0.3
## [9] evaluate_1.0.1 grid_4.3.3 estimability_1.5.1 mvtnorm_1.2-4
## [13] fastmap_1.2.0 Matrix_1.6-5 jsonlite_1.8.9 survival_3.5-8
## [17] multcomp_1.4-25 purrr_1.0.2 fansi_1.0.6 scales_1.3.0
## [21] TH.data_1.1-2 codetools_0.2-20 jquerylib_0.1.4 cli_3.6.3
## [25] crayon_1.5.2 rlang_1.1.4 bit64_4.0.5 splines_4.3.3
## [29] munsell_0.5.1 withr_3.0.2 cachem_1.1.0 yaml_2.3.10
## [33] parallel_4.3.3 tools_4.3.3 datawizard_0.10.0 tzdb_0.4.0
## [37] coda_0.19-4.1 colorspace_2.1-1 ggplot2_3.5.1 bayestestR_0.13.2
## [41] vctrs_0.6.5 R6_2.5.1 zoo_1.8-12 lifecycle_1.0.4
## [45] emmeans_1.10.2 bit_4.0.5 vroom_1.6.5 MASS_7.3-60.0.1
## [49] pkgconfig_2.0.3 pillar_1.9.0 bslib_0.8.0 gtable_0.3.6
## [53] glue_1.8.0 xfun_0.49 tibble_3.2.1 tidyselect_1.2.1
## [57] rstudioapi_0.17.1 parameters_0.21.6 knitr_1.49 farver_2.1.2
## [61] xtable_1.8-4 htmltools_0.5.8.1 labeling_0.4.3 rmarkdown_2.29
## [65] compiler_4.3.3